{"id":"W4387770710","doi":"10.21203/rs.3.rs-3448044/v1","title":"Data Security and Privacy Research Trends: LDA Topic Modeling","year":2023,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Malware Detection Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Big data; Computer science; Expansive; Data science; Encryption; Cloud computing; Internet privacy; Information privacy; The Internet; Computer security; World Wide Web; Data mining","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.01664244,0.0008396723,0.001170446,0.02340134,0.001461185,0.008348058,0.001048694,0.001245641,0.003112532],"category_scores_gemma":[0.05399628,0.0004688748,0.002828116,0.02980421,0.001298774,0.005530292,0.002599538,0.0021638,0.001468186],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002923334,"about_ca_system_score_gemma":0.004594258,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006885802,"about_ca_topic_score_gemma":0.005236956,"domain_scores_codex":[0.9884991,0.006603928,0.001033352,0.001355522,0.002074909,0.0004332164],"domain_scores_gemma":[0.9337559,0.0520015,0.00422613,0.002456875,0.006864954,0.0006946744],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0008265344,0.0004462596,0.2315142,0.009575767,0.001649764,0.0006704008,0.01705693,0.01480836,0.003957046,0.08780611,0.04334299,0.5883456],"study_design_scores_gemma":[0.0002035852,0.0005276762,0.1538309,0.00744976,0.002223478,0.002028384,0.02851358,0.3250298,0.006467238,0.2510588,0.2222796,0.0003872145],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3410027,0.1018482,0.4481883,0.03769625,0.001106705,0.002070747,0.02924941,0.002029142,0.03680846],"genre_scores_gemma":[0.8607579,0.02395118,0.09652473,0.001038577,0.0009491647,0.00154564,0.0109146,0.0002073009,0.004110915],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9765987,"threshold_uncertainty_score":0.08801466,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4510731732612783,"score_gpt":0.5333456925675857,"score_spread":0.08227251930630741,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}